Mapping catchment-scale unmonitored groundwater abstractions: Approaches based on soft data

Vu, H.M.; Shanafield, Margaret; Nhat, Tran Thong; Partington, Daniel; Batelaan, Okke

doi:10.1016/j.ejrh.2020.100695

Cited by 7 publications

(6 citation statements)

References 18 publications

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“…For example, in Denmark, Thorling et al (2012) indicated that the water withdrawal data, registered in the Danish groundwater database Jupiter, are often inadequate because abstractions from irrigation wells and other private wells are often missing. Consequently, information on accurate abstraction volumes remains largely deceptive because actual groundwater withdrawal rates are seldom equal to the permitted rates (Vu et al 2020).…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, alternative approaches to estimating groundwater withdrawals are necessary (Vu et al 2020). In this study, both potential transpiration and groundwater use were lumped together as

draft

(m 3 /a), leading to the following water budget equation (Genereux et al 2005; Yihdego and Khalil 2017; Vu et al 2020):

{italicGW}_{r} = draft + {italicBF}_{a} \pm ∆ S,

where the

{italicGW}_{r}

is a groundwater recharge (m 3 /a),

{italicBF}_{a}

is an actual groundwater contribution to streamflow (m 3 /a), and

∆ S

is a dimensionless change in storage (m 3 /a). This approach derives

draft

after all other components of the groundwater balance have been estimated (Vu et al 2020).…”

Section: Methodsmentioning

confidence: 99%

“…Consequently, it is difficult to estimate potential groundwater transpiration (Miller et al 2007;Heilweil and Brooks 2011). Therefore, alternative approaches to estimating groundwater withdrawals are necessary (Vu et al 2020). In this study, both potential transpiration and groundwater use were lumped together as draft (m 3 /a), leading to the following water budget equation (Genereux et al 2005;Yihdego and Khalil 2017;Vu et al 2020):…”

Section: Groundwater Budgetmentioning

confidence: 99%

“…where the GW r is a groundwater recharge (m 3 /a), BF a is an actual groundwater contribution to streamflow (m 3 /a), and S is a dimensionless change in storage (m 3 /a). This approach derives draft after all other components of the groundwater balance have been estimated (Vu et al 2020). The use of the groundwater budget equation this way is related to its simplicity and its being easily adaptable as it relies on a few assumptions on groundwater flow and storage (Healy et al 2007).…”

Section: Groundwater Budgetmentioning

confidence: 99%

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Catchment‐Wide Groundwater Budget for the Inkomati‐Usuthu Water Management Area in South Africa

Shakhane,

Mojabake

2024

Groundwater

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In South Africa, approximately 98% of the predicted total surface water resources are already being used up. Consequently, the National Water Resource Strategy considers groundwater to be important for the future planning and management of water resources. In this case, quantifying groundwater budgets is a prerequisite because they provide a means for evaluating the availability and sustainability of a water supply. This study estimated the regional groundwater budgets for the Inkomati‐Usuthu Water Management Area (Usuthu, Komati, Sabie‐Sand, and Crocodile) using the classical hydrological continuity equation. The equation was used to describe prevailing feedback loops between groundwater draft, recharge, baseflow, and storage change. The results were coarser scale estimates which, beforehand, were derived from the 2006 study. In the years to follow, groundwater reliance intensified and there was also the historic 2015/2016 drought. This inevitably led to an increased draft while the rest of the components of the groundwater budgets experienced decreases. Both Crocodile and Sabie‐Sand experienced groundwater storage depletion which led to reduced baseflow and groundwater availability, while groundwater recharge contrarily increased due to capture. Conversely, the other two catchments experienced relatively lower drafts with correspondingly higher groundwater availability and recharge while storage change was positive. The results highlighted the need for adaptive water management whose effectiveness relies on predictive studies. Consequently, future models should be developed to capture the spatial and temporal dynamism of the natural groundwater budget due to climate change, water demands, and population growth predictions.

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Section: Methodsmentioning

confidence: 99%

“…Therefore, alternative approaches to estimating groundwater withdrawals are necessary (Vu et al 2020). In this study, both potential transpiration and groundwater use were lumped together as

draft

(m 3 /a), leading to the following water budget equation (Genereux et al 2005; Yihdego and Khalil 2017; Vu et al 2020):

{italicGW}_{r} = draft + {italicBF}_{a} \pm ∆ S,

where the

{italicGW}_{r}

is a groundwater recharge (m 3 /a),

{italicBF}_{a}

is an actual groundwater contribution to streamflow (m 3 /a), and

∆ S

is a dimensionless change in storage (m 3 /a). This approach derives

draft

after all other components of the groundwater balance have been estimated (Vu et al 2020).…”

Section: Methodsmentioning

confidence: 99%

Section: Groundwater Budgetmentioning

confidence: 99%

Section: Groundwater Budgetmentioning

confidence: 99%

See 2 more Smart Citations

Catchment‐Wide Groundwater Budget for the Inkomati‐Usuthu Water Management Area in South Africa

Shakhane,

Mojabake

2024

Groundwater

View full text Add to dashboard Cite

show abstract

“…The WetSpass model in the GIS environment, which integrates all hydrological processes, has become an excellent option for dealing with more complex hydrological factors in small catchments (Gebru and Tesfahunegn, 2020). This model has been used successfully in various studies around the world (Graf and Przybylek, 2014;Melki et al, 2017;Molla et al, 2019;Ashaolu et al, 2020;Vu et al, 2020). In this study, the monthly water balance is investigated using the WetSpass-M distribution model.…”

Section: Introductionmentioning

confidence: 99%

Investigating spatial and temporal trend of groundwater quality in relation to water balance components (A case study of Chaharmahal va Bakhtiari Province, Iran)

Zamani‐Ahmadmahmoodi

Bayati

Abdollahi

et al. 2022

Preprint

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One of the problems of water resources in Iran is excessive drop in groundwater level, in which Chaharmahal va Bakhtiari province, located in this country, is no exception․ In this study, the trend of spatial and temporal changes in groundwater quality and water balance and the relationship between them in this province were investigated. The WetSpass-M distribution model was used due to the capability of distribution models in simulating watershed hydrological processes. The results showed good accuracy of the model in simulating runoff and basal flow of the study basin. The trend of water quality changes was investigated by calculating the IRWQI index and preparing its zoning maps. For this purpose, 132 samples of well water in different areas of the study were prepared in 2007 to 2017. Spatial distribution maps showed that the groundwater quality in the north and northeast of the region was lower than in other parts. Also, groundwater quality had declined over time. In rangeland, groundwater quality was better and nitrate level was lower than in agriculture and buildup land uses. Also, the relationship between nitrate and drought with water quality was seen due to the similar color pattern in their zoning maps in the region. The correlation between groundwater quality parameters and water balance components also showed a weak correlation on an annual scale and a strong correlation between some parameters in some wells on a monthly scale.

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Investigating spatial and temporal trend of groundwater quality in relation to water balance in 2007–2017: a case study of Chaharmahal va Bakhtiari Province, Iran

Zamani-Ahmadmahmoodi,

Bayati,

Abdollahi

et al. 2023

Appl Water Sci

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The extensive exploitation of water resources in Chaharmahal va Bakhtiari province has led to a destructive impact on the water balance and quality of the region. In order to evaluate water quality of the study area, water quality parameters from 132 wells were analyzed to prepare spatial distribution maps of the IRWQI index. To analyze spatial and temporal rainfall anomalies, the SPI index was spatially interpolated using the ordinary Kriging method. Principal component analysis was used to investigate the relationship between water quality parameters. The suitability of data for PCA was evaluated by the Kaiser–Meyer–Olkin and Bartlett tests. Additionally, water balance components of the study area, including surface runoff and ground water, were simulated using the WetSpass-M model. According to the results of the IRWQI index, 54 wells, mostly located in built-up and agricultural lands, had poor quality․ Investigation of the average groundwater quality during the years 2007 to 2017 shows that the trend of groundwater quality decreased. Comparison of drought and water quality maps showed similar patterns so that in areas with extreme drought, water quality was bad. The highest and lowest recorded concentrations for nitrates were related to built-up and rangeland lands with concentrations of 35 and 21 mg/l, respectively. Comparison among land use classes showed that in the rangelands, groundwater quality was better and nitrate level was lower compared to agricultural and built-up areas. Overall, the results of this study show that water quality can be affected by land use types and water balance components.

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Mapping catchment-scale unmonitored groundwater abstractions: Approaches based on soft data

Cited by 7 publications

References 18 publications

Catchment‐Wide Groundwater Budget for the Inkomati‐Usuthu Water Management Area in South Africa

Catchment‐Wide Groundwater Budget for the Inkomati‐Usuthu Water Management Area in South Africa

Investigating spatial and temporal trend of groundwater quality in relation to water balance components (A case study of Chaharmahal va Bakhtiari Province, Iran)

Investigating spatial and temporal trend of groundwater quality in relation to water balance in 2007–2017: a case study of Chaharmahal va Bakhtiari Province, Iran

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